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- Title
Gait Parameter and Speed Estimation from the Frontal View Gait Video Data Based on the Gait Motion and Spatial Modeling.
- Authors
Okusa, Kosuke; Kamakura, Toshinari
- Abstract
We study the problem of analyzing and classifying frontal view gait video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameters. We estimate these parameters using the statistical registration and modeling on a video data. Our gait model is based on human gait structure and temporal-spatial relations between camera and subject. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the proposed method in gait analysis for young/elderly person and abnormal gait detection. In abnormal gait detection experiment, we apply K-nearestneighbor classifier, using the estimated parameters, to perform normal/abnormal gait detect, and present results from an experiment involving 120 subjects (young person), and 60 subjects (elderly person). As a result, our method shows high detection rate.
- Subjects
PARAMETER estimation; SPEED measurements; GAIT disorders; DATA analysis; STATISTICS; MATHEMATICAL models
- Publication
IAENG International Journal of Applied Mathematics, 2013, Vol 43, Issue 1, p37
- ISSN
1992-9978
- Publication type
Article